scholarly journals Aerosol modelling in Europe with a focus on Switzerland during summer and winter episodes

2011 ◽  
Vol 11 (14) ◽  
pp. 7355-7373 ◽  
Author(s):  
S. Aksoyoglu ◽  
J. Keller ◽  
I. Barmpadimos ◽  
D. Oderbolz ◽  
V. A. Lanz ◽  
...  
Keyword(s):  
Air Quality ◽  
Organic Aerosol ◽  
Oxidation Products ◽  
Base Case ◽  
Chemical Compositions ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model ◽  
Aerosol Composition ◽  
Sensitivity Tests

Abstract. This paper describes aerosol modelling in Europe with a focus on Switzerland during summer and winter periods. We modelled PM2.5 (particles smaller than 2.5 μm in aerodynamic diameter) for one summer and two winter periods in years 2006 and 2007 using the CAMx air quality model. The meteorological fields were obtained from MM5 simulations. The modelled wind speeds during some low-wind periods, however, had to be calibrated with measurements to use realistic input for the air quality model. The detailed AMS (aerosol mass spectrometer) measurements at specific locations were used to evaluate the model results. In addition to the base case simulations, we carried out sensitivity tests with modified aerosol precursor emissions, air temperature and deposition. Aerosol concentrations in winter 2006 were twice as high as those in winter 2007, however, the chemical compositions were similar. CAMx could reproduce the relative composition of aerosols very well both in the winter and summer periods. Absolute concentrations of aerosol species were underestimated by about 20 %. Both measurements and model results suggest that organic aerosol (30–38 %) and particulate nitrate (30–36 %) are the main aerosol components in winter. In summer, organic aerosol dominates the aerosol composition (55–57 %) and is mainly of secondary origin. The contribution of biogenic volatile organic compound (BVOC) emissions to the formation of secondary organic aerosol (SOA) was predicted to be very large (>95 %) in Switzerland. The main contributors to the modelled SOA concentrations were oxidation products of monoterpenes and sesquiterpenes as well as oligomerization of oxidized compounds. The fraction of primary organic aerosol (POA) derived from measurements was lower than the model predictions indicating the importance of volatility of POA, which has not yet been taken into account in CAMx. Sensitivity tests with reduced NOx and NH3 emissions suggest that aerosol formation is more sensitive to ammonia emissions in winter in a large part of Europe. In Switzerland however, aerosol formation is predicted to be NOx-sensitive. In summer, effects of NOx and NH3 emission reductions on aerosol concentrations are predicted to be lower mostly due to lower ammonium nitrate concentrations. In general, the sensitivity to NH3 emissions is weaker in summer due to higher NH3 emissions.

scholarly journals Aerosol modelling in Europe with a focus on Switzerland during summer and winter episodes

2011 ◽  
Vol 11 (4) ◽  
pp. 10799-10844
Author(s):  
S. Aksoyoglu ◽  
J. Keller ◽  
I. Barmpadimos ◽  
D. Oderbolz ◽  
V. A. Lanz ◽  
...  
Keyword(s):  
Organic Aerosol ◽  
Oxidation Products ◽  
Base Case ◽  
Chemical Compositions ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model ◽  
Aerosol Composition ◽  
Nh3 Emission ◽  
Sensitivity Tests

Abstract. This paper describes aerosol modelling in Europe with a focus on Switzerland during summer and winter periods. We modelled PM2.5 (particles smaller than 2.5 μm in aerodynamic diameter) for one summer and two winter periods in years 2006 and 2007 using the MM5/CAMx air quality model system. The detailed AMS (aerosol mass spectrometer) measurements at specific locations were used to evaluate the model results. In addition to the base case simulations, we carried out sensitivity tests with modified aerosol precursor emissions, air temperature and deposition. Aerosol concentrations in winter 2006 were twice as high as those in winter 2007, however, the chemical compositions were similar. CAMx could reproduce the relative composition of aerosols very well both in the winter and summer periods. Absolute concentrations of aerosol species were underestimated by about 20%. Both measurements and model results suggest that organic aerosol (30–38%) and particulate nitrate (30–36%) are the main aerosol components in winter. In summer, organic aerosol dominates the aerosol composition (55–57%) and is mainly of secondary origin. The contribution of biogenic volatile organic compound (BVOC) emissions to the formation of secondary organic aerosol (SOA) was predicted to be very large (>95%) in Switzerland. The main contributors to the modelled SOA concentrations were oxidation products of monoterpenes and sesquiterpenes as well as oligomerization of oxidized compounds. The fraction of primary organic aerosol (POA) derived from measurements was lower than the model predictions indicating the importance of volatility of POA, which has not yet been taken into account in CAMx. Sensitivity tests with reduced NOx and NH3 emissions suggest that aerosol formation is more sensitive to ammonia emissions in winter in a large part of Europe. In Switzerland however, aerosol formation is predicted to be NOx-sensitive. In summer, effects of NOx and NH3 emission reductions on aerosol concentrations are predicted to be lower mostly due to lower ammonium nitrate concentrations. In general, the sensitivity to NH3 emissions is weaker in summer due to higher NH3 emissions.

scholarly journals Modeling organic aerosols in a megacity: potential contribution of semi-volatile and intermediate volatility primary organic compounds to secondary organic aerosol formation

2010 ◽  
Vol 10 (12) ◽  
pp. 5491-5514 ◽  
Author(s):  
A. Hodzic ◽  
J. L. Jimenez ◽  
S. Madronich ◽  
M. R. Canagaratna ◽  
P. F. DeCarlo ◽  
...  
Keyword(s):  
Organic Aerosols ◽  
Oxidation Products ◽  
Sufficient Evidence ◽  
Base Case ◽  
Potential Contribution ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model ◽  
Diurnal Variability ◽  
The City

Abstract. It has been established that observed local and regional levels of secondary organic aerosols (SOA) in polluted areas cannot be explained by the oxidation and partitioning of anthropogenic and biogenic VOC precursors, at least using current mechanisms and parameterizations. In this study, the 3-D regional air quality model CHIMERE is applied to estimate the potential contribution to SOA formation of recently identified semi-volatile and intermediate volatility organic precursors (S/IVOC) in and around Mexico City for the MILAGRO field experiment during March 2006. The model has been updated to include explicitly the volatility distribution of primary organic aerosols (POA), their gas-particle partitioning and the gas-phase oxidation of the vapors. Two recently proposed parameterizations, those of Robinson et al. (2007) ("ROB") and Grieshop et al. (2009) ("GRI") are compared and evaluated against surface and aircraft measurements. The 3-D model results are assessed by comparing with the concentrations of OA components from Positive Matrix Factorization of Aerosol Mass Spectrometer (AMS) data, and for the first time also with oxygen-to-carbon ratios derived from high-resolution AMS measurements. The results show a substantial enhancement in predicted SOA concentrations (2–4 times) with respect to the previously published base case without S/IVOCs (Hodzic et al., 2009), both within and downwind of the city leading to much reduced discrepancies with the total OA measurements. Model improvements in OA predictions are associated with the better-captured SOA magnitude and diurnal variability. The predicted production from anthropogenic and biomass burning S/IVOC represents 40–60% of the total measured SOA at the surface during the day and is somewhat larger than that from commonly measured aromatic VOCs, especially at the T1 site at the edge of the city. The SOA production from the continued multi-generation S/IVOC oxidation products continues actively downwind. Similar to aircraft observations, the predicted OA/ΔCO ratio for the ROB case increases from 20–30 μg sm−3 ppm−1 up to 60–70 μg sm−3 ppm−1 between a fresh and 1-day aged air mass, while the GRI case produces a 30% higher OA growth than observed. The predicted average O/C ratio of total OA for the ROB case is 0.16 at T0, substantially below observed value of 0.5. A much better agreement for O/C ratios and temporal variability (R2=0.63) is achieved with the updated GRI treatment. Both treatments show a deficiency in regard to POA ageing with a tendency to over-evaporate POA upon dilution of the urban plume suggesting that atmospheric HOA may be less volatile than assumed in these parameterizations. This study highlights the important potential role of S/IVOC chemistry in the SOA budget in this region, and highlights the need for further improvements in available parameterizations. The agreement observed in this study is not sufficient evidence to conclude that S/IVOC are the major missing SOA source in megacity environments. The model is still very underconstrained, and other possible pathways such as formation from very volatile species like glyoxal may explain some of the mass and especially increase the O/C ratio.

scholarly journals Exploring the nature of air quality over southwestern Ontario: main findings from the Border Air Quality and Meteorology Study

2013 ◽  
Vol 13 (20) ◽  
pp. 10461-10482 ◽  
Author(s):  
J. R. Brook ◽  
P. A. Makar ◽  
D. M. L. Sills ◽  
K. L. Hayden ◽  
R. McLaren
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Great Lakes ◽  
The United States ◽  
Urban Heat Islands ◽  
Anthropogenic Emissions ◽  
Lake Breeze ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model

Abstract. This paper serves as an overview and discusses the main findings from the Border Air Quality and Meteorology Study (BAQS-Met) in southwestern Ontario in 2007. This region is dominated by the Great Lakes, shares borders with the United States and consistently experiences the highest ozone (O3) and fine particulate matter concentrations in Canada. The purpose of BAQS-Met was to improve our understanding of how lake-driven meteorology impacts air quality in the region, and to improve models used for forecasting and policy scenarios. Results show that lake breeze occurrence frequencies and inland penetration distances were significantly greater than realized in the past. Due to their effect on local meteorology, the lakes were found to enhance secondary O3 and aerosol formation such that local anthropogenic emissions have their impact closer to the populated source areas than would otherwise occur in the absence of the lakes. Substantial spatial heterogeneity in O3 was observed with local peaks typically 30 ppb above the regional values. Sulfate and secondary organic aerosol (SOA) enhancements were also linked to local emissions being transported in the lake breeze circulations. This study included the first detailed evaluation of regional applications of a high-resolution (2.5 km grid) air quality model in the Great Lakes region. The model showed that maxima in secondary pollutants occur in areas of convergence, in localized updrafts and in distinct pockets over the lake surfaces. These effects are caused by lake circulations interacting with the synoptic flow, with each other or with circulations induced by urban heat islands. Biogenic and anthropogenic emissions were both shown to play a role in the formation of SOA in the region. Detailed particle measurements and multivariate receptor models reveal that while individual particles are internally mixed, they often exist within more complex external mixtures. This makes it difficult to predict aerosol optical properties and further highlights the challenges facing aerosol modelling. The BAQS-Met study has led to a better understanding of the value of high-resolution (2.5 km) modelling for air quality and meteorological predictions and has led to several model improvements.

Regional source apportionment of ozone and PM2.5 during the EXPLORE-YRD campaign in the Yangtze River Delta region of China

2020 ◽  
Author(s):  
Jianlin Hu ◽  
Lin Li ◽  
Jingyi Li ◽  
Xueying Wang ◽  
Kangjia Gong
Keyword(s):  
Air Quality ◽  
Yangtze River Delta ◽  
River Delta ◽  
Formation Mechanisms ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model ◽  
Haze Pollution ◽  
Source Category ◽  
The Yrd

<p>Although the air quality in China has been improved by collaborative efforts dedicating to mitigate the haze pollution, PM2.5 concentrations still remain high levels and the issue of increasing O<sub>3</sub> concentration has attracted more attention of the public. The YRD region has been suffering from both the PM2.5 and O3 pollution problems. To investigate the formation mechanisms and sources of PM2.5 and O3 in this region, a comprehensive EXPLORE-YRD campaign (EXPeriment on the eLucidation of theatmospheric Oxidation capacity and aerosol foRmation, and their Effects inYangtze River Delta) was carried out in May - June 2018. In this study, we investigate the contributions of different source categories to PM2.5 and O<sub>3</sub>. A source-oriented 3-D air quality model (CMAQ) was applied to analyze contributions of different emission sources to PM2.5 and O<sub>3 </sub>in the YRD region. Emissions were divided into eight source categories: industry, power, transportation, residential, agriculture, biogenic, wildfire, and other countries. Contribution from individual source category was quantified. The importance of anthropogenic and natural sources to PM2.5 and O<sub>3</sub> was discussed.</p>

scholarly journals Evaluation of European air quality modelled by CAMx including the volatility basis set scheme

2016 ◽  
Vol 16 (16) ◽  
pp. 10313-10332 ◽  
Author(s):  
Giancarlo Ciarelli ◽  
Sebnem Aksoyoglu ◽  
Monica Crippa ◽  
Jose-Luis Jimenez ◽  
Eriko Nemitz ◽  
...  
Keyword(s):  
Air Quality ◽  
Measurement Data ◽  
Model Performance ◽  
Monitoring And Evaluation ◽  
Basis Set ◽  
Air Quality Model ◽  
Quality Model ◽  
Aerosol Mass ◽  
Sensitivity Tests ◽  
Compensation Of Errors

Abstract. Four periods of EMEP (European Monitoring and Evaluation Programme) intensive measurement campaigns (June 2006, January 2007, September–October 2008 and February–March 2009) were modelled using the regional air quality model CAMx with VBS (volatility basis set) approach for the first time in Europe within the framework of the EURODELTA-III model intercomparison exercise. More detailed analysis and sensitivity tests were performed for the period of February–March 2009 and June 2006 to investigate the uncertainties in emissions as well as to improve the modelling of organic aerosol (OA). Model performance for selected gas phase species and PM2.5 was evaluated using the European air quality database AirBase. Sulfur dioxide (SO2) and ozone (O3) were found to be overestimated for all the four periods, with O3 having the largest mean bias during June 2006 and January–February 2007 periods (8.9 pbb and 12.3 ppb mean biases respectively). In contrast, nitrogen dioxide (NO2) and carbon monoxide (CO) were found to be underestimated for all the four periods. CAMx reproduced both total concentrations and monthly variations of PM2.5 for all the four periods with average biases ranging from −2.1 to 1.0 µg m−3. Comparisons with AMS (aerosol mass spectrometer) measurements at different sites in Europe during February–March 2009 showed that in general the model overpredicts the inorganic aerosol fraction and underpredicts the organic one, such that the good agreement for PM2.5 is partly due to compensation of errors. The effect of the choice of VBS scheme on OA was investigated as well. Two sensitivity tests with volatility distributions based on previous chamber and ambient measurements data were performed. For February–March 2009 the chamber case reduced the total OA concentrations by about 42 % on average. In contrast, a test based on ambient measurement data increased OA concentrations by about 42 % for the same period bringing model and observations into better agreement. Comparison with the AMS data at the rural Swiss site Payerne in June 2006 shows no significant improvement in modelled OA concentration. Further sensitivity tests with increased biogenic and anthropogenic emissions suggest that OA in Payerne was affected by changes in emissions from residential heating during the February–March 2009 whereas it was more sensitive to biogenic precursors in June 2006.

scholarly journals Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50

2021 ◽  
Vol 14 (3) ◽  
pp. 1681-1697
Author(s):  
Jianhui Jiang ◽  
Imad El Haddad ◽  
Sebnem Aksoyoglu ◽  
Giulia Stefenelli ◽  
Amelie Bertrand ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Experimental Studies ◽  
Organic Aerosol ◽  
Basis Set ◽  
Reference Scenario ◽  
Air Quality Model ◽  
Quality Model ◽  
The Balkans ◽  
Wall Loss

Abstract. Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models that use parameters obtained from chamber experiments. In this study, a box model with a volatility basis set (VBS) scheme was developed, and the secondary organic aerosol (SOA) yields with vapor wall loss correction were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9–4.9 and leads to better agreement with measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The model results from the VBS schemes with standard (VBS_BASE) and vapor-wall-loss-corrected parameters (VBS_WLS), as well as the traditional two-product approach, were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM) or aerosol mass spectrometer (AMS) stations in the winter of 2011. An additional reference scenario, VBS_noWLS, was also developed using the same parameterization as VBS_WLS except for the SOA yields, which were optimized by assuming there is no vapor wall loss. The VBS_WLS generally shows the best performance for predicting OA among all OA schemes and reduces the mean fractional bias from −72.9 % (VBS_BASE) to −1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µg m−3), which is 106.6 % and 26.2 % higher than VBS_BASE and VBS_noWLS, respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ∼80 % (in the Balkans). VBS_WLS also leads to better agreement between the modeled SOA fraction in OA (fSOA) and the estimated values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in parameterizations based on laboratory studies for a wider range of chamber conditions and field observations with higher spatial and temporal coverage.

scholarly journals Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 2: Assessing the influence of vapor wall losses

2015 ◽  
Vol 15 (21) ◽  
pp. 30081-30126 ◽  
Author(s):  
C. D. Cappa ◽  
S. H. Jathar ◽  
M. J. Kleeman ◽  
K. S. Docherty ◽  
J. L. Jimenez ◽  
...  
Keyword(s):  
Air Quality ◽  
Secondary Organic Aerosol ◽  
Organic Aerosol ◽  
Air Quality Model ◽  
Quality Model ◽  
Wall Losses ◽  
Regional Air Quality ◽  
High Vapor ◽  
Wall Loss ◽  
Oxidation Model

Abstract. The influence of losses of organic vapors to chamber walls during secondary organic aerosol (SOA) formation experiments has recently been established. Here, the influence of such losses on simulated ambient SOA concentrations and properties is assessed in the UCD/CIT regional air quality model using the statistical oxidation model (SOM) for SOA. The SOM was fit to laboratory chamber data both with and without accounting for vapor wall losses following the approach of Zhang et al. (2014). Two vapor wall loss scenarios are considered when fitting of SOM to chamber data to determine best-fit SOM parameters, one with "low" and one with "high" vapor wall-loss rates to approximately account for the current range of uncertainty in this process. Simulations were run using these different parameterizations (scenarios) for both the southern California/South Coast Air Basin (SoCAB) and the eastern United States (US). Accounting for vapor wall losses leads to substantial increases in the simulated SOA concentrations from VOCs in both domains, by factors of ~ 2–5 for the low and ~ 5–10 for the high scenario. The magnitude of the increase scales approximately inversely with the absolute SOA concentration of the no loss scenario. In SoCAB, the predicted SOA fraction of total OA increases from ~ 0.2 (no) to ~ 0.5 (low) and to ~ 0.7 (high), with the high vapor wall loss simulations providing best general agreement with observations. In the eastern US, the SOA fraction is large in all cases but increases further when vapor wall losses are accounted for. The total OA/ΔCO ratio represents dilution-corrected SOA concentrations. The simulated OA/ΔCO in SoCAB (specifically, at Riverside, CA) is found to increase substantially during the day only for the high vapor wall loss scenario, which is consistent with observations and indicative of photochemical production of SOA. Simulated O : C atomic ratios for both SOA and for total OA increase when vapor wall losses are accounted for, while simulated H : C atomic ratios decrease. The agreement between simulations and observations of both the absolute values and the diurnal profile of the O : C and H : C atomic ratios for total OA was greatly improved when vapor wall-losses were accounted for. Similar improvements would likely not be possible solely through the inclusion of semi/intermediate volatility organic compounds in the simulations. These results overall demonstrate that vapor wall losses in chambers have the potential to exert a large influence on simulated ambient SOA concentrations, and further suggest that accounting for such effects in models can explain a number of different observations and model/measurement discrepancies.

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